Energy-Aware Autonomic Resource Allocation in Multitier Virtualized Environments
With the increase of energy consumption associated with IT infrastructures, energy management is becoming a priority in the design and operation of complex service-based systems. At the same time, service providers need to comply with Service Level Agreement (SLA) contracts which determine the reven...
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| Vydané v: | IEEE transactions on services computing Ročník 5; číslo 1; s. 2 - 19 |
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| Hlavní autori: | , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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IEEE
01.01.2012
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| ISSN: | 1939-1374, 2372-0204 |
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| Abstract | With the increase of energy consumption associated with IT infrastructures, energy management is becoming a priority in the design and operation of complex service-based systems. At the same time, service providers need to comply with Service Level Agreement (SLA) contracts which determine the revenues and penalties on the basis of the achieved performance level. This paper focuses on the resource allocation problem in multitier virtualized systems with the goal of maximizing the SLAs revenue while minimizing energy costs. The main novelty of our approach is to address-in a unifying framework-service centers resource management by exploiting as actuation mechanisms allocation of virtual machines (VMs) to servers, load balancing, capacity allocation, server power state tuning, and dynamic voltage/frequency scaling. Resource management is modeled as an NP-hard mixed integer nonlinear programming problem, and solved by a local search procedure. To validate its effectiveness, the proposed model is compared to top-performing state-of-the-art techniques. The evaluation is based on simulation and on real experiments performed in a prototype environment. Synthetic as well as realistic workloads and a number of different scenarios of interest are considered. Results show that we are able to yield significant revenue gains for the provider when compared to alternative methods (up to 45 percent). Moreover, solutions are robust to service time and workload variations. |
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| AbstractList | With the increase of energy consumption associated with IT infrastructures, energy management is becoming a priority in the design and operation of complex service-based systems. At the same time, service providers need to comply with Service Level Agreement (SLA) contracts which determine the revenues and penalties on the basis of the achieved performance level. This paper focuses on the resource allocation problem in multitier virtualized systems with the goal of maximizing the SLAs revenue while minimizing energy costs. The main novelty of our approach is to address-in a unifying framework-service centers resource management by exploiting as actuation mechanisms allocation of virtual machines (VMs) to servers, load balancing, capacity allocation, server power state tuning, and dynamic voltage/frequency scaling. Resource management is modeled as an NP-hard mixed integer nonlinear programming problem, and solved by a local search procedure. To validate its effectiveness, the proposed model is compared to top-performing state-of-the-art techniques. The evaluation is based on simulation and on real experiments performed in a prototype environment. Synthetic as well as realistic workloads and a number of different scenarios of interest are considered. Results show that we are able to yield significant revenue gains for the provider when compared to alternative methods (up to 45 percent). Moreover, solutions are robust to service time and workload variations. |
| Author | Panicucci, B. Li Zhang Ardagna, D. Trubian, M. |
| Author_xml | – sequence: 1 givenname: D. surname: Ardagna fullname: Ardagna, D. email: ardagna@elet.polimi.it organization: Dipt. di Elettron. e Inf., Politec. di Milano, Milan, Italy – sequence: 2 givenname: B. surname: Panicucci fullname: Panicucci, B. email: panicucci@elet.polimi.it organization: Dipt. di Elettron. e Inf., Politec. di Milano, Milan, Italy – sequence: 3 givenname: M. surname: Trubian fullname: Trubian, M. email: trubian@dsi.unimi.it organization: Dipt. di Sci. dell'Inf., Univ. degli Studi di Milano, Milan, Italy – sequence: 4 surname: Li Zhang fullname: Li Zhang email: zhangli@us.ibm.com organization: IBM T.J. Watson Res. Center, Yorktown Heights, NY, USA |
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| SubjectTerms | Energy consumption energy cost reduction Load management Load modeling Machine learning Optimization Performance attributes performance of systems quality concepts resource allocation Resource management Servers |
| Title | Energy-Aware Autonomic Resource Allocation in Multitier Virtualized Environments |
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